Downloads · 30 days
4
14% of all-time downloads
Mistral-7B_final_MT
rishavranaut/Mistral-7B_final_MT
Mistral-7B_final_MT is a machine learning model from rishavranaut. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
28
Public
Repo size
547 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors54.6 MB · 96%
At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Oct 22, 2024
- Updated
- Oct 23, 2024
- SHA
- 785d90c7
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
Mistral-7B_final_MT
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7471
- Accuracy: 0.8
- Precision: 0.7795
- Recall: 0.8367
- F1 score: 0.8071
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 score |
|---|---|---|---|---|---|---|---|
| 1.2073 | 0.5 | 200 | 1.0465 | 0.6867 | 0.7857 | 0.5133 | 0.6210 |
| 0.8334 | 1.0 | 400 | 0.8003 | 0.7317 | 0.7456 | 0.7033 | 0.7238 |
| 0.4526 | 1.5 | 600 | 0.8224 | 0.7433 | 0.7074 | 0.83 | 0.7638 |
| 0.4306 | 2.0 | 800 | 0.8715 | 0.7467 | 0.8895 | 0.5633 | 0.6898 |
| 0.296 | 2.5 | 1000 | 0.6957 | 0.7767 | 0.7441 | 0.8433 | 0.7906 |
| 0.2864 | 3.0 | 1200 | 0.6663 | 0.7983 | 0.8163 | 0.77 | 0.7925 |
| 0.1803 | 3.5 | 1400 | 0.6645 | 0.8 | 0.8082 | 0.7867 | 0.7973 |
| 0.1603 | 4.0 | 1600 | 0.6943 | 0.7833 | 0.7560 | 0.8367 | 0.7943 |
| 0.0907 | 4.5 | 1800 | 0.7265 | 0.81 | 0.7981 | 0.83 | 0.8137 |
| 0.0798 | 5.0 | 2000 | 0.7471 | 0.8 | 0.7795 | 0.8367 | 0.8071 |
Framework versions
- PEFT 0.11.1
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Oct 22, 2024
- Updated
- Oct 23, 2024